Context Window

Compare

GPT-5 Pro vs Meta Llama3 2 11b Instruct

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Openai

Model

GPT-5 Pro

Image inputTool calling

Context window

400K

400,000 tokens · ~300K words

Model page
Meta

Model

Meta Llama3 2 11b Instruct

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

GPT-5 Pro400K
Meta Llama3 2 11b Instruct128K

GPT-5 Pro has about 3.1× the context window of the other in this pair.

Token calculator →Memory savings →

GPT-5 Pro has 212% more context capacity (400K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GPT-5 Pro. Its 400K context fits entire documents without chunking (vs 128K).

  • Long output (reports, code files)

    Use GPT-5 Pro. Its 128K max output lets you generate complete artifacts in one request.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecGPT-5 ProMeta Llama3 2 11b Instruct
Context window400,000 tokens (400K)128,000 tokens (128K)
Max output tokens128,000 tokens (128K)4,096 tokens (4K)
Speed tierBalancedFast
VisionYesYes
Function callingYesYes
Extended thinkingYesNo
Prompt cachingNoNo
Batch APINoNo
Release dateOct 2025N/A

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderGPT-5 Pro inGPT-5 Pro outMeta Llama3 2 11b Instruct inMeta Llama3 2 11b Instruct out
Aws Bedrock——$0.350/M$0.350/M

Frequently asked questions

GPT-5 Pro has a larger context window: 400K tokens vs 128K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Calculate your savingsLearn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model